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Data Engineer, ORBIT (AMZL operational reporting and BI)

External
Amazon.com Services LLC logoAmazon.com · Austin, TX
Full-timeOn-site1mo ago
PythonJavaScalaSQLAWS
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Requirements

  • 3+ years of data engineering experience
  • 2+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
  • 2+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
  • Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Experience building large-scale, high-throughput, 24x7 data systems
  • Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Additional Information

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon's customers, achieving on-time delivery in a cost-effective manner. Amazon is looking for a passionate, results-oriented Data Engineer to help build the next generation of analytics for Amazon Logistics. In this role, you will work at the intersection of data engineering and AI to transform how Last Mile decisions are made. You will design and build scalable data systems and contribute to agentic solutions that enable leaders to access insights, metrics, and root cause analysis in a seamless and intuitive way. As a Data Engineer on the Orbit (AMZL operational reporting and BI) team, you will operate in one of the most complex data and agentic solution environments at Amazon. You will focus on organizing and structuring large-scale datasets that power critical business metrics across Last Mile delivery, while enabling AI-driven use cases such as automated insights, RCA generation, and conversational analytics. You will work with modern AWS technologies and evolving AI capabilities (e.g., Bedrock, event-driven architectures, real-time data systems) to build reliable, low-latency, and cost-efficient data solutions. This is a high-impact role where you will partner closely with product, engineers, and business stakeholders to translate complex requirements into scalable data products. You will thrive here if you: 1. Are excited about building data solutions that power AI and agentic workflows 2. Continuously learn and apply new technologies to solve real business problems 3. Can design simple, scalable solutions in complex and ambiguous environments 4. Care deeply about data quality, ownership, and building reliable systems at scale Key job responsibilities 1. Build and deploy agentic AI solutions to improve Last Mile analytics and decision-making 2. Continuously evaluate and adopt evolving AI/ML technologies (e.g., Bedrock, Bedrock Agents / AgentCore, other AWS Services) and apply them to real business problems 3. Own and drive data quality initiatives for Lastmile, focusing on scalable and reliable solutions 4. Help the team scale by building simple, maintainable systems and mentoring junior engineers


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